Once deployed, foundation models can be scaled, managed, and governed in production using Vertex AI’s end-to-end MLOps capabilities and fully-managed AI infrastructure. We provide a wide range of tools, automated workflows, and starting points. Generative AI support in Vertex AI makes it easier for developers and data scientists to access, customize, and deploy foundation models from a simple user interface. To date, it’s been difficult to access generative AI and customize foundation models for business use cases because managing these large models in production is a difficult task, requiring an advanced toolkit, lots of data, specialized skills, and even more time. Realizing the potential of this technology means putting it in the hands of every developer, business, and government. In the last few months, consumer-grade generative AI has captured the attention of millions, with intelligent chatbots and lifelike digital avatars. Now it’s possible to harness the full power of generative AI built directly in our end-to-end machine learning platform. Generative AI support in Vertex AI offers the simplest way for teams to take advantage of an array of generative models. Since then, customers like Wayfair, Vodafone, Twitter, and CNA have accelerated their ML projects with Vertex AI, and we’ve released hundreds of new features.īut we didn’t stop there - Vertex AI recently had its biggest update yet. Vertex AI was launched in 2021 to help fast-track ML model development and deployment, from feature engineering to model training to low-latency inference, all with enterprise governance and monitoring. But dancing or not, I’m really excited about Generative AI support in Vertex AI. My suggestion was turned down, and I'm sure you’re as disappointed as I am. Okay, so I initially suggested that I deliver the content of this blog as an interpretive dance video.
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